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  • 1. Caulfield, Thomas R.
    et al.
    Fiesel, Fabienne C.
    Moussaud-Lamodiere, Elisabeth L.
    Dourado, Daniel F. A. R.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology.
    Flores, Samuel C.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology.
    Springer, Wolfdieter
    Phosphorylation by PINK1 Releases the UBL Domain and Initializes the Conformational Opening of the E3 Ubiquitin Ligase Parkin2014In: PloS Computational Biology, ISSN 1553-734X, E-ISSN 1553-7358, Vol. 10, no 11, p. e1003935-Article in journal (Refereed)
    Abstract [en]

    Loss-of-function mutations in PINK1 or PARKIN are the most common causes of autosomal recessive Parkinson's disease. Both gene products, the Ser/Thr kinase PINK1 and the E3 Ubiquitin ligase Parkin, functionally cooperate in a mitochondrial quality control pathway. Upon stress, PINK1 activates Parkin and enables its translocation to and ubiquitination of damaged mitochondria to facilitate their clearance from the cell. Though PINK1-dependent phosphorylation of Ser65 is an important initial step, the molecular mechanisms underlying the activation of Parkin's enzymatic functions remain unclear. Using molecular modeling, we generated a complete structural model of human Parkin at all atom resolution. At steady state, the Ub ligase is maintained inactive in a closed, auto-inhibited conformation that results from intra-molecular interactions. Evidently, Parkin has to undergo major structural rearrangements in order to unleash its catalytic activity. As a spark, we have modeled PINK1-dependent Ser65 phosphorylation in silico and provide the first molecular dynamics simulation of Parkin conformations along a sequential unfolding pathway that could release its intertwined domains and enable its catalytic activity. We combined free (unbiased) molecular dynamics simulation, Monte Carlo algorithms, and minimalbiasing methods with cell-based high content imaging and biochemical assays. Phosphorylation of Ser65 results in widening of a newly defined cleft and dissociation of the regulatory N-terminal UBL domain. This motion propagates through further opening conformations that allow binding of an Ub-loaded E2 co-enzyme. Subsequent spatial reorientation of the catalytic centers of both enzymes might facilitate the transfer of the Ub moiety to charge Parkin. Our structure-function study provides the basis to elucidate regulatory mechanisms and activity of the neuroprotective Parkin. This may open up new avenues for the development of small molecule Parkin activators through targeted drug design.

  • 2. Cruz, Jose Almeida
    et al.
    Blanchet, Marc-Frederick
    Boniecki, Michal
    Bujnicki, Janusz M.
    Chen, Shi-Jie
    Cao, Song
    Das, Rhiju
    Ding, Feng
    Dokholyan, Nikolay V.
    Coulbourn Flores, Samuel
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology.
    Huang, Lili
    Lavender, Christopher A.
    Lisi, Veronique
    Major, Francois
    Mikolajczak, Katarzyna
    Patel, Dinshaw J.
    Philips, Anna
    Puton, Tomasz
    Santalucia, John
    Sijenyi, Fredrick
    Hermann, Thomas
    Rother, Kristian
    Rother, Magdalena
    Serganov, Alexander
    Skorupski, Marcin
    Soltysinski, Tomasz
    Sripakdeevong, Parin
    Tuszynska, Irina
    Weeks, Kevin M.
    Waldsich, Christina
    Wildauer, Michael
    Leontis, Neocles B.
    Westhof, Eric
    RNA-Puzzles: A CASP-like evaluation of RNA three-dimensional structure prediction2012In: RNA: A publication of the RNA Society, ISSN 1355-8382, E-ISSN 1469-9001, Vol. 18, no 4, p. 610-625Article in journal (Refereed)
    Abstract [en]

    We report the results of a first, collective, blind experiment in RNA three-dimensional (3D) structure prediction, encompassing three prediction puzzles. The goals are to assess the leading edge of RNA structure prediction techniques; compare existing methods and tools; and evaluate their relative strengths, weaknesses, and limitations in terms of sequence length and structural complexity. The results should give potential users insight into the suitability of available methods for different applications and facilitate efforts in the RNA structure prediction community in ongoing efforts to improve prediction tools. We also report the creation of an automated evaluation pipeline to facilitate the analysis of future RNA structure prediction exercises.

  • 3.
    Dourado, Daniel F. A. R.
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology.
    Flores, Samuel Coulbourn
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology.
    A multiscale approach to predicting affinity changes in protein-protein interfaces2014In: Proteins: Structure, Function, and Bioinformatics, ISSN 0887-3585, E-ISSN 1097-0134, Vol. 82, no 10, p. 2681-2690Article in journal (Refereed)
    Abstract [en]

    Substitution mutations in protein-protein interfaces can have a substantial effect on binding, which has consequences in basic and applied biomedical research. Experimental expression, purification, and affinity determination of protein complexes is an expensive and time-consuming means of evaluating the effect of mutations, making a fast and accurate in silico method highly desirable. When the structure of the wild-type complex is known, it is possible to economically evaluate the effect of point mutations with knowledge based potentials, which do not model backbone flexibility, but these have been validated only for single mutants. Substitution mutations tend to induce local conformational rearrangements only. Accordingly, ZEMu (Zone Equilibration of Mutants) flexibilizes only a small region around the site of mutation, then computes its dynamics under a physics-based force field. We validate with 1254 experimental mutants (with 1-15 simultaneous substitutions) in a wide variety of different protein environments (65 protein complexes), and obtain a significant improvement in the accuracy of predicted Delta Delta G.

  • 4.
    Dourado, Daniel F. A. R.
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics.
    Flores, Samuel Coulbourn
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics.
    Modeling and fitting protein-protein complexes to predict change of binding energy2016In: Scientific Reports, ISSN 2045-2322, E-ISSN 2045-2322, Vol. 6, article id 25406Article in journal (Refereed)
    Abstract [en]

    It is possible to accurately and economically predict change in protein-protein interaction energy upon mutation (Delta Delta G), when a high-resolution structure of the complex is available. This is of growing usefulness for design of high-affinity or otherwise modified binding proteins for therapeutic, diagnostic, industrial, and basic science applications. Recently the field has begun to pursue Delta Delta G prediction for homology modeled complexes, but so far this has worked mostly for cases of high sequence identity. If the interacting proteins have been crystallized in free (uncomplexed) form, in a majority of cases it is possible to find a structurally similar complex which can be used as the basis for template-based modeling. We describe how to use MMB to create such models, and then use them to predict Delta Delta G, using a dataset consisting of free target structures, co-crystallized template complexes with sequence identify with respect to the targets as low as 44%, and experimental Delta Delta G measurements. We obtain similar results by fitting to a low-resolution Cryo-EM density map. Results suggest that other structural constraints may lead to a similar outcome, making the method even more broadly applicable.

  • 5. Fiesel, Fabienne C.
    et al.
    Caulfield, Thomas R.
    Moussaud-Lamodiere, Elisabeth L.
    Ogaki, Kotaro
    Dourado, Daniel F. A. R.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology.
    Flores, Samuel C.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology.
    Ross, Owen A.
    Springer, Wolfdieter
    Structural and Functional Impact of Parkinson Disease-Associated Mutations in the E3 Ubiquitin Ligase Parkin2015In: Human Mutation, ISSN 1059-7794, E-ISSN 1098-1004, Vol. 36, no 8, p. 774-786Article in journal (Refereed)
    Abstract [en]

    Mutations in the PARKIN/PARK2 gene that result in loss-of-function of the encoded, neuroprotective E3 ubiquitin ligase Parkin cause recessive, familial early-onset Parkinson disease. As an increasing number of rare Parkin sequence variants with unclear pathogenicity are identified, structure-function analyses will be critical to determine their disease relevance. Depending on the specific amino acids affected, several distinct pathomechanisms can result in loss of Parkin function. These include disruption of overall Parkin folding, decreased solubility, and protein aggregation. However pathogenic effects can also result from misregulation of Parkin autoinhibition and of its enzymatic functions. In addition, interference of binding to coenzymes, substrates, and adaptor proteins can affect its catalytic activity too. Herein, we have performed a comprehensive structural and functional analysis of 21 PARK2 missense mutations distributed across the individual protein domains. Using this combined approach, we were able to pinpoint some of the pathogenic mechanisms of individual sequence variants. Similar analyses will be critical in gaining a complete understanding of the complex regulations and enzymatic functions of Parkin. These studies will not only highlight the important residues, but will also help to develop novel therapeutics aimed at activating and preserving an active, neuroprotective form of Parkin.

  • 6. Flores, Samuel
    FlexOracle: predicting flexible hinges by identification of stable domains2007In: BMC Bioinformatics, ISSN 1471-2105, E-ISSN 1471-2105, Vol. 8, p. 215-Article in journal (Refereed)
  • 7. Flores, Samuel
    Hinge Atlas: relating sequence features to sites of structural flexibility2007In: BMC Bioinformatics, ISSN 1471-2105, E-ISSN 1471-2105, Vol. 8, p. 167-Article in journal (Refereed)
  • 8. Flores, Samuel
    HingeMaster: Normal mode hinge prediction approach and integration of complementary predictors2008In: Proteins: Structure, Function, and Bioinformatics, Vol. 73, p. 299-319Article in journal (Refereed)
  • 9. Flores, Samuel
    Predicting RNA stucture by multiple template homology modeling2010In: Pacific Symposium on Biocomputing, p. 216-227Article in journal (Refereed)
  • 10. Flores, Samuel
    StoneHinge: hinge prediction by network analysis of individual protein structures2009In: Protein Science, ISSN 0961-8368, E-ISSN 1469-896X, Vol. 18, p. 359-371Article in journal (Refereed)
  • 11. Flores, Samuel
    Turning limited experimental information into 3D models of RNA2010In: RNA: A publication of the RNA Society, ISSN 1355-8382, E-ISSN 1469-9001, Vol. 16, no 9, p. 1769-1778Article in journal (Refereed)
  • 12. Flores, Samuel
    et al.
    Altman, Russ
    Stanford University.
    Structural insights into pre-translocation ribosome motions2011In: Proceedings of the Pacific Symposium on BiocomputingArticle in journal (Refereed)
  • 13.
    Flores, Samuel
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology.
    Bernauer, Julie
    INRIA.
    Shin, Seokmin
    Chemistry Department of Seoul National University.
    Zhou, Ruhong
    Huang, Xuhui
    Department of Chemistry, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong.
    Multiscale modeling of macromolecular biosystems2012In: Briefings in Bioinformatics, ISSN 1467-5463, E-ISSN 1477-4054, Vol. 13, no 4, p. 395-405Article in journal (Refereed)
    Abstract [en]

    In this article, we review the recent progress in multiresolution modeling of structure and dynamics of protein, RNA and their complexes. Many approaches using both physics-based and knowledge-based potentials have been developed at multiple granularities to model both protein and RNA. Coarse graining can be achieved not only in the length, but also in the time domain using discrete time and discrete state kinetic network models. Models with different resolutions can be combined either in a sequential or parallel fashion. Similarly, the modeling of assemblies is also often achieved using multiple granularities.The progress shows that a multiresolution approach has considerable potential to continue extending the length and time scales of macromolecular modeling.

  • 14.
    Flores, Samuel C.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology.
    Elucidating Ribosomal Translocation with Internal Coordinate Flexible Fitting2014In: Biophysical Journal, ISSN 0006-3495, E-ISSN 1542-0086, Vol. 106, no 2, p. 492A-493AArticle in journal (Other academic)
    Abstract [en]

    Determining conformational changes of large macromolecules is challenging experimentally and computationally. The ribosome has been observed crystallographically in several states but many others have been seen only by low-resolution methods including cryo-electron microscopy. Meanwhile the crucial dynamics between states remain out of reach of experimental structure determination methods. Most existing computational approaches model complexes at all-atom resolution, at very high cost, or use approximations which lose some of the most interesting dynamical details. I have developed Internal Coordinate Flexible Fitting (ICFF), a multiscale method that uses full atomic forces and flexibility only in key regions of a model, capturing extensive conformational rearrangements at low cost. I use ICFF to turn low-resolution density maps, crystallographic structures, and biochemical information into the largest-scale all-atoms trajectory of ribosomal translocation modeled to date. ICFF is three orders of magnitude faster than the most comparable existing method. The results suggest an intriguing possible mechanism of translocation.

  • 15.
    Flores, Samuel Coulbourn
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology.
    Fast fitting to low resolution density maps: elucidating large-scale motions of the ribosome2014In: Nucleic Acids Research, ISSN 0305-1048, E-ISSN 1362-4962, Vol. 42, no 2, p. e9-Article in journal (Refereed)
    Abstract [en]

    Determining the conformational rearrangements of large macromolecules is challenging experimentally and computationally. Case in point is the ribosome; it has been observed by high-resolution crystallography in several states, but many others are known only from low-resolution methods including cryoelectron microscopy. Combining these data into dynamical trajectories that may aid understanding of its largest-scale conformational changes has so far remained out of reach of computational methods. Most existing methods either model all atoms explicitly, resulting in often prohibitive cost, or use approximations that lose interesting structural and dynamical detail. In this work, I introduce Internal Coordinate Flexible Fitting, which uses full atomic forces and flexibility in limited regions of a model, capturing extensive conformational rearrangements at low cost. I use it to turn multiple low-resolution density maps, crystallographic structures and biochemical information into unified all-atoms trajectories of ribosomal translocation. Internal Coordinate Flexible Fitting is three orders of magnitude faster than the most comparable existing method.

  • 16.
    Flores, Samuel
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology.
    Gerstein, Mark
    Yale University.
    Predicting protein ligand binding motions with the Conformation Explorer2011In: BMC Bioinformatics, ISSN 1471-2105, E-ISSN 1471-2105, Vol. 12, p. 417-Article in journal (Refereed)
    Abstract [en]

    Background

    Knowledge of the structure of proteins bound to known or potential ligands is crucial for biological understanding and drug design. Often the 3D structure of the protein is available in some conformation, but binding the ligand of interest may involve a large scale conformational change which is difficult to predict with existing methods.

    Results

    We describe how to generate ligand binding conformations of proteins that move by hinge bending, the largest class of motions. First, we predict the location of the hinge between domains. Second, we apply an Euler rotation to one of the domains about the hinge point. Third, we compute a short-time dynamical trajectory using Molecular Dynamics to equilibrate the protein and ligand and correct unnatural atomic positions. Fourth, we score the generated structures using a novel fitness function which favors closed or holo structures. By iterating the second through fourth steps we systematically minimize the fitness function, thus predicting the conformational change required for small ligand binding for five well studied proteins.

    Conclusions

    We demonstrate that the method in most cases successfully predicts the holo conformation given only an apo structure.

  • 17.
    Flores, Samuel
    et al.
    Stanford University.
    Jonikas, Magdalena
    Stanford University.
    Methods for building and refining 3D models of RNA2012In: "RNA 3D Structure Analysis and Prediction / [ed] Neocles Leontis and Eric Westhof, Springer London, 2012, 1Chapter in book (Other academic)
  • 18. Flores, Samuel
    et al.
    Sherman, Michael
    Stanford University.
    Fast flexible modeling of RNA structure using internal coordinates2011In: Transactions in Computational Biology and BioinformaticsArticle in journal (Refereed)
  • 19.
    Flores, Samuel
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology.
    Zemora, Georgeta
    Waldsich, Christina
    Insights into diseases of human telomerase from dynamical modeling2013In: / [ed] Russ Altman, 2013, p. 200-211Conference paper (Refereed)
    Abstract [en]

    Mutations in the telomerase complex disrupt either nucleic acid binding or catalysis, and are the cause of numerous human diseases. Despite its importance, the structure of the human telomerase complex has not been observed crystallographically, nor are its dynamics understood in detail. Fragments of this complex from Tetrahymena thermophila and Tribolium castaneum have been crystallized. Biochemical probes provide important insight into dynamics. In this work we summarize evidence that the T. castaneum structure is Telomerase Reverse Transcriptase. We use this structure to build a partial model of the human Telomerase complex. The model suggests an explanation for the structural role of several disease-associated mutations. We then generate a 3D kinematic trajectory of telomere elongation to illustrate a "typewriter" mechanism: the RNA template moves to keep the end of the growing telomeric primer in the active site, disengaging after every 6-residue extension to execute a "carriage return" and go back to its starting position. A hairpin can easily form in the primer, from DNA residues leaving the primer-template duplex. The trajectory is consistent with available experimental evidence. The methodology is extensible to many problems in structural biology in general and personalized medicine in particular.

  • 20.
    Koripella, Ravi Kiran
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Structure and Molecular Biology.
    Holm, Mikael
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Structure and Molecular Biology.
    Dourado, Daniel
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology.
    Mandava, Chandra Sekhar
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Structure and Molecular Biology.
    Flores, Samuel
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology.
    Sanyal, Suparna
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Structure and Molecular Biology.
    A conserved histidine in switch-II of EF-G moderates release of inorganic phosphate2015In: Scientific Reports, ISSN 2045-2322, E-ISSN 2045-2322, Vol. 5, article id 12970Article in journal (Refereed)
    Abstract [en]

    Elongation factor G (EF-G), a translational GTPase responsible for tRNA-mRNA translocation possesses a conserved histidine (H91 in Escherichia coli) at the apex of switch-II, which has been implicated in GTPase activation and GTP hydrolysis. While H91A, H91R and H91E mutants showed different degrees of defect in ribosome associated GTP hydrolysis, H91Q behaved like the WT. However, all these mutants, including H91Q, are much more defective in inorganic phosphate (Pi) release, thereby suggesting that H91 facilitates Pi release. In crystal structures of the ribosome bound EF-G center dot GTP a tight coupling between H91 and the gamma-phosphate of GTP can be seen. Following GTP hydrolysis, H91 flips similar to 140 degrees in the opposite direction, probably with Pi still coupled to it. This, we suggest, promotes Pi to detach from GDP and reach the inter-domain space of EF-G, which constitutes an exit path for the Pi. Molecular dynamics simulations are consistent with this hypothesis and demonstrate a vital role of an Mg2+ ion in the process.

  • 21. Moretti, Rocco
    et al.
    Fleishman, Sarel J.
    Agius, Rudi
    Torchala, Mieczyslaw
    Bates, Paul A.
    Kastritis, Panagiotis L.
    Rodrigues, Joao P. G. L. M.
    Trellet, Mikael
    Bonvin, Alexandre M. J. J.
    Cui, Meng
    Rooman, Marianne
    Gillis, Dimitri
    Dehouck, Yves
    Moal, Iain
    Romero-Durana, Miguel
    Perez-Cano, Laura
    Pallara, Chiara
    Jimenez, Brian
    Fernandez-Recio, Juan
    Flores, Samuel
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology.
    Pacella, Michael
    Kilambi, Krishna Praneeth
    Gray, Jeffrey J.
    Popov, Petr
    Grudinin, Sergei
    Esquivel-Rodriguez, Juan
    Kihara, Daisuke
    Zhao, Nan
    Korkin, Dmitry
    Zhu, Xiaolei
    Demerdash, Omar N. A.
    Mitchell, Julie C.
    Kanamori, Eiji
    Tsuchiya, Yuko
    Nakamura, Haruki
    Lee, Hasup
    Park, Hahnbeom
    Seok, Chaok
    Sarmiento, Jamica
    Liang, Shide
    Teraguchi, Shusuke
    Standley, Daron M.
    Shimoyama, Hiromitsu
    Terashi, Genki
    Takeda-Shitaka, Mayuko
    Iwadate, Mitsuo
    Umeyama, Hideaki
    Beglov, Dmitri
    Hall, David R.
    Kozakov, Dima
    Vajda, Sandor
    Pierce, Brian G.
    Hwang, Howook
    Vreven, Thom
    Weng, Zhiping
    Huang, Yangyu
    Li, Haotian
    Yang, Xiufeng
    Ji, Xiaofeng
    Liu, Shiyong
    Xiao, Yi
    Zacharias, Martin
    Qin, Sanbo
    Zhou, Huan-Xiang
    Huang, Sheng-You
    Zou, Xiaoqin
    Velankar, Sameer
    Janin, Joel
    Wodak, Shoshana J.
    Baker, David
    Community-wide evaluation of methods for predicting the effect of mutations on protein-protein interactions2013In: Proteins: Structure, Function, and Bioinformatics, ISSN 0887-3585, E-ISSN 1097-0134, Vol. 81, no 11, p. 1980-1987Article in journal (Refereed)
    Abstract [en]

    Community-wide blind prediction experiments such as CAPRI and CASP provide an objective measure of the current state of predictive methodology. Here we describe a community-wide assessment of methods to predict the effects of mutations on protein-protein interactions. Twenty-two groups predicted the effects of comprehensive saturation mutagenesis for two designed influenza hemagglutinin binders and the results were compared with experimental yeast display enrichment data obtained using deep sequencing. The most successful methods explicitly considered the effects of mutation on monomer stability in addition to binding affinity, carried out explicit side-chain sampling and backbone relaxation, evaluated packing, electrostatic, and solvation effects, and correctly identified around a third of the beneficial mutations. Much room for improvement remains for even the best techniques, and large-scale fitness landscapes should continue to provide an excellent test bed for continued evaluation of both existing and new prediction methodologies. Proteins 2013; 81:1980-1987.

  • 22.
    Nosrati, Masoumeh
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Microbiology. Ferdowsi Univ Mashhad, Dept Chem, Mashhad, Iran.
    Solbak, Sara
    Uppsala University, Disciplinary Domain of Science and Technology, Chemistry, Department of Chemistry - BMC, Biochemistry.
    Nordesjö, Olle
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology.
    Nissbeck, Mikael
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Microbiology.
    Dourado, Daniel F. A. R.
    Uppsala University, Disciplinary Domain of Science and Technology, Chemistry, Department of Chemistry - BMC, Biochemistry.
    Andersson, Ken G
    Royal Institute of Technology, Stockholm, Sweden.
    Housaindokht, Mohammad Reza
    Ferdowsi University of Mashhad, Mashhad, Iran.
    Löfblom, John
    Royal Institute of Technology, Stockholm, Sweden.
    Virtanen, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Microbiology.
    Danielson, U. Helena
    Uppsala University, Disciplinary Domain of Science and Technology, Chemistry, Department of Chemistry - BMC, Biochemistry.
    Flores, Samuel Coulbourn
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology.
    Insights from engineering the Affibody-Fc interaction with a computational-experimental method2017In: Protein Engineering Design & Selection, ISSN 1741-0126, E-ISSN 1741-0134, Vol. 30, no 9, p. 593-601Article in journal (Refereed)
    Abstract [en]

    The interaction between the Staphylococcal Protein A (SpA) domain B (the basis of the Affibody) molecule and the Fc of IgG is key to the use of Affibodies in affinity chromatography and in potential therapies against certain inflammatory diseases. Despite its importance and four-decade history, to our knowledge this interaction has never been affinity matured. We elucidate reasons why single-substitutions in the SpA which improve affinity to Fc may be very rare, and also discover substitutions which potentially serve several engineering purposes. We used a variation of FoldX to predict changes in protein-protein-binding affinity, and produce a list of 41 single-amino acid substitutions on the SpA molecule, of which four are near wild type (wt) and five are at most a factor of four from wt affinity. The nine substitutions include one which removes lysine, and several others which change charge. Subtle modulations in affinity may be useful for modifying column elution conditions. The method is applicable to other protein-protein systems, providing molecular insights with lower workload than existing experimental techniques.

  • 23.
    Tek, Alex
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology.
    Chen, Yang
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Structure and Molecular Biology.
    Selmer, Maria
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Structure and Molecular Biology.
    Flores, Samuel C.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology.
    Investigating Ribosome Conformations with Multi-Resolution Modeling2014In: Biophysical Journal, ISSN 0006-3495, E-ISSN 1542-0086, Vol. 106, no 2, p. 491A-491AArticle in journal (Other academic)
  • 24.
    Tek, Alex
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology.
    Korostelev, Andrei A.
    Univ Massachusetts, Sch Med, Dept Biochem & Mol Pharmacol, RNA Therapeut Inst, 368 Plantat St, Worcester, MA 01605 USA..
    Flores, Samuel Coulbourn
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology.
    MMB-GUI: a fast morphing method demonstrates a possible ribosomal tRNA translocation trajectory2016In: Nucleic Acids Research, ISSN 0305-1048, E-ISSN 1362-4962, Vol. 44, no 1, p. 95-105Article in journal (Refereed)
    Abstract [en]

    Easy-to-use macromolecular viewers, such as UCSF Chimera, are a standard tool in structural biology. They allow rendering and performing geometric operations on large complexes, such as viruses and ribosomes. Dynamical simulation codes enable modeling of conformational changes, but may require considerable time and many CPUs. There is an unmet demand from structural and molecular biologists for software in the middle ground, which would allow visualization combined with quick and interactive modeling of conformational changes, even of large complexes. This motivates MMB-GUI. MMB uses an internal-coordinate, multiscale approach, yielding as much as a 2000-fold speedup over conventional simulation methods. We use Chimera as an interactive graphical interface to control MMB. We show how this can be used for morphing of macromolecules that can be heterogeneous in biopolymer type, sequence, and chain count, accurately recapitulating structural intermediates. We use MMB-GUI to create a possible trajectory of EF-G mediated gate-passing translocation in the ribosome, with all-atom structures. This shows that the GUI makes modeling of large macromolecules accessible to a wide audience. The morph highlights similarities in tRNA conformational changes as tRNA translocates from A to P and from P to E sites and suggests that tRNA flexibility is critical for translocation completion.

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